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2022 Clean Power Research, LLC. The Importance of Data Quality for Reducing the Uncertainty of Site-Adapted Solar Resource Datasets Patrick Keelin | Lead Product Manager August 23, 2022 20 years advancing the energy transformation Clean Power Research Team Industries ServedExpertise 65 Electric Utilities Energy Agencies IOUs Munis Co-ops 200 Solar Industry Partners Independent engineers Solar financiers, operators, installers Utility planners 75 employees HQ Kirkland, WA Research Napa, CA Satellites NY MA 20 people with advanced degrees Engineering/Environment/Resources Meteorology/Atmospheric Science Business Secure, enterprise-grade cloud software Focus Renewable energy DERs, EVs and beyond Solar data intelligence Patents 44 granted, 18 pending Partnered with Dr. Perez SUNY Albany v021622 Powering Intelligent Energy Decisions for the Solar Industry Equivalent solar dataset validation years Influencing 90 of U.S. solar development Delivering 10M API data requests per month Winner of double-blind EPRI forecast trial Operational data services provided for 1M PV systems 10GW of solar 90 10M 11M 1,074 replace with photo, see slide 19 for instructions Serving the industry’s leading enterprises 200 v021622 Background - What is a tuning study Tuning methodology Kankiewicz, A., Wu, E., Dise, J., Perez, R., 2014 Reducing Solar Project Uncertainty with an Optimized Resource Assessment Tuning Methodology. Proc., ASES Solar 2014 Conference, San Francisco, California Background - What is a tuning study Tuning methodology Kankiewicz, A., Wu, E., Dise, J., Perez, R., 2014 Reducing Solar Project Uncertainty with an Optimized Resource Assessment Tuning Methodology. Proc., ASES Solar 2014 Conference, San Francisco, California Background - What is a tuning study Tuning methodology Kankiewicz, A., Wu, E., Dise, J., Perez, R., 2014 Reducing Solar Project Uncertainty with an Optimized Resource Assessment Tuning Methodology. Proc., ASES Solar 2014 Conference, San Francisco, California Background - What is a tuning study Tuning uncertainty 2.00 Background - Tuning uncertainty J. Alfi, A. Kubiniec, G. Mani, J. Christopherson, Y. He and J. Bosch, “Importance of input data and uncertainty associated with tuning satellite to ground solar irradiation,“ 2016 IEEE 43rd Photovoltaic Specialists Conference PVSC, 2016, pp. 0301-0305, doi 10.1109/PVSC.2016.7749598. Motivation for an updated study What’s the best achievable today Improved ground-data QC methods SolarAnywhere model updates Experience with hundreds of projects Why does solar resource data quality matter Short Validation 1998 2022 Annu al Inso lation Resource Data Dataset B Dataset A On-site data Correlation On-site data Dataset B Dataset A Correlation Tuned Resource Data Why does solar resource data quality matter Short Validation Complete Validation 1998 2022 Annu al Inso lation On-site data On-site data Dataset B Dataset A SolarAnywhere Correlation Correlation Resource Data 2020 PV Systems Symposium Webinar Satellite Irradiance Model Accuracy Improvements Clean Power Research See also Eva Plaza Sanz Peter Johnson UL Multiple Satellite Models for On-Site Long-Term References Updated study design Same as original study Tuning procedure Study methodology but expanded period, 1998 – 2021 SURFRAD, 2011- 2021 SOLRAD Test Datasets V3.2 to approximate original study Improved ground-data QC V3.6 latest Expanded geography – Europe Results Results QC similar to BSRN recommended quality checks. See https//bsrn.awi.de/en/data/quality-checks SolarAnywhere model improvements 2015 2016 2017 2018 2019 2020 2021 2022 Tuning methods published V3.2 IR image processing V3.4 Time series monthly aerosols V3.5 Time series hourly aerosols V3.3 Satellite hardware calibration V3.6 5min x 500m imagery Selected features Results Bottom line Results Additional sources of solar resource uncertainty Reference measurement uncertainty Resource shift DNI and DHI transposition to plane of array Other environmental factors e.g., snow, soiling, albedo, shading Modeling errors e.g., sub-hourly clipping Learn more Tuning Study Resources https//www.solaranywhere.com/resources/webinars-whitepapers/ground-tuning-studies https//pvpmc.sandia.gov/resources-and-events/events/ Follow Clean Power Research on LinkedIn Upcoming webinar – High Res. Data http//ow.ly/FOcw50Kh87V The information contained in this presentation is confidential. Thank You Questions Patrick Keelin | pkeelincleanpower.com